Five AI Compute Architectures Every Engineer Should Know: CPUs, GPUs, TPUs, NPUs, and LPUs Compared

The article compares CPUs, GPUs, TPUs, NPUs, and LPUs and shows how each is optimized for different AI workloads.

CPUs are best for orchestration and general-purpose tasks, while GPUs and TPUs excel at parallel computation and training.

NPUs target on-device inference, and LPUs are designed for ultra-low-latency inference, making workload fit crucial.

As AI systems shift toward specialized hardware, engineers need to weigh performance and efficiency trade-offs when choosing compute.